svist4get: a simple visualization tool for genomic tracks from sequencing experiments

• Published in: BMC bioinformatics Vol. 20; no. 1; pp. 113 - 6
• Main Authors: Egorov, Artyom A., Sakharova, Ekaterina A., Anisimova, Aleksandra S., Dmitriev, Sergey E., Gladyshev, Vadim N., Kulakovskiy, Ivan V.
• Format: Journal Article
• Language: English
• Published: London BioMed Central 06.03.2019; BioMed Central Ltd; Springer Nature B.V; BMC
• Subjects: Acids; Algorithms; Analysis; Annotations; Bioinformatics; Biomedical and Life Sciences; Computational biology; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Computer graphics; Computer programs; Data analysis; Data processing; DNA sequencing; Experiments; Gene expression; Gene mapping; Genome; Genomes; Genomic tracks; Genomics; Genomics - methods; Graphical user interface; High-Throughput Nucleotide Sequencing - methods; High-throughput sequencing; image analysis and data visualization; Image resolution; Imaging; Life Sciences; Line interfaces; Mapping; Methods; Microarrays; Molecular biology; Next-generation sequencing; Ribo-Seq; Ribonucleic acid; Ribosomes - metabolism; RNA; RNA sequencing; RNA, Messenger - genetics; RNA, Messenger - metabolism; RNA-Seq; Software; Software development tools; Source code; Technology application; Tracking; User interface; Visualization; Visualization (Computer); Web browsers; Russia; Visualization; Next-generation sequencing; Genome browser; High-throughput sequencing; RNA-Seq; Genomic tracks; Ribo-Seq; Python
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-019-2706-8

Background High-throughput sequencing often provides a foundation for experimental analyses in the life sciences. For many such methods, an intermediate layer of bioinformatics data analysis is the genomic signal track constructed by short read mapping to a particular genome assembly. There are many software tools to visualize genomic tracks in a web browser or with a stand-alone graphical user interface. However, there are only few command-line applications suitable for automated usage or production of publication-ready visualizations. Results Here we present svist4get, a command-line tool for customizable generation of publication-quality figures based on data from genomic signal tracks. Similarly to generic genome browser software, svist4get visualizes signal tracks at a given genomic location and is able to aggregate data from several tracks on a single plot along with the transcriptome annotation. The resulting plots can be saved as the vector or high-resolution bitmap images. We demonstrate practical use cases of svist4get for Ribo-Seq and RNA-Seq data. Conclusions svist4get is implemented in Python 3 and runs on Linux. The command-line interface of svist4get allows for easy integration into bioinformatics pipelines in a console environment. Extra customization is possible through configuration files and Python API. For convenience, svist4get is provided as pypi package. The source code is available at https://bitbucket.org/artegorov/svist4get/